P2P

90 AI AS YOUR TRIAGE PARTNER Because these timelines can span hundreds of hours of footage, AI now plays a critical role in surfacing the key moments that matter. According to Maura Grossman and Judge Paul Grimm's article on judicial approaches to AI-generated evidence, modern AI models can tag speakers, detect tone shifts, and flag potential escalation or anomalies in large multimedia collections. Duke Law's "How to Keep Deepfakes Out of Court" similarly emphasizes that AI can help isolate noteworthy events while human reviewers retain responsibility for legal judgment. In practice, this means AI helps surface the two or three key minutes inside a hundred-hour video so reviewers can stay focused on what matters. In my experience, AI has been remarkably effective at locating obscure or damaged objects in video or photos, identifying speakers in old court recordings filled with overlapping and chaotic noise, and automatically flagging swearing, hate speech, personally identifiable information (PII), and other sensitive content. This makes it an incredibly useful tool for identifying relevant data sources and isolating key moments inside massive multimedia evidence datasets. WHAT SMART LEGAL TEAMS ARE DOING NOW Bringing these principles into day-to-day practice requires structured workflows that anticipate authenticity challenges before they arise. Several practices are emerging as best practices: • Evidence-based design: According to commentary on Federal Rule of Evidence 902(14) from firms like Robins Kaplan and authors such as Toft, organizations should ensure CCTV, body cams, mobile devices, and IoT sensors use consistent time and location settings; even a minor timestamp drift can damage defensibility. • Timeline‑first workflows: As Dixon and Ferraro & Gurney both argue, it is not enough to store video. You need tools that normalize formats, sync streams, and support annotation and comparison so the full narrative becomes clear. • AI as a force multiplier: Following the guidance of Grossman, Grimm, and others, smart teams use AI to flag meaningful moments, like when new speakers enter the conversation, the tone changes, or there is an escalation in sound or movement. • Deepfake-aware and ready: Drawing on standards work by the Coalition for Content Provenance and Authenticity (C2PA), forward-thinking teams assume AI-related objections are coming and plan in advance: A. Provenance standards (like C2PA): According to C2PA's "Verifying Media Content Sources," open standards can encode where media originated and how it has been altered. B. Cryptographic signing: As described in C2PA's specification announcement, cryptographic signing can help ensure that any modification leaves a detectable trace. C. Forensic validation: C2PA and related technical FAQs note that hardware-backed attestation and forensic review can help confirm that a source device is genuine and trustworthy. According to the C2PA FAQ, provenance is essentially the metadata story of an evidence file. It shows when it was created, how it moved, and whether anything changed along the way. AI now plays a critical role in surfacing the key moments that matter.

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